Non-Parametric Estimation of Location

Abstract

A sequence of asymptotically normally distributed estimators of location is presented, having the property that, for any epsilon > 0, all estimators in the sequence beyond an appropriate point have asymptotic variances within epsilon of the Cramer-Rao lower bound, uniformly for all symmetric distributions in a non-parametric family constrained only by regularity conditions. The simplest non-trivial estimator in this sequence already possesses good efficiency-robustness properties, both asymptotically and for small sample sizes. This estimator is much easier to compute than previously proposed estimators having similar properties, and a good non-parametric estimate of the variance of the location estimator is produced as a byproduct.

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Document Details

Document Type
Technical Report
Publication Date
Nov 02, 1971
Accession Number
AD0737620

Entities

People

  • M. V. Johns Jr.

Organizations

  • Stanford University

Tags

Communities of Interest

  • C4I
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Asymptotic Normality
  • California
  • Classification
  • Coefficients
  • Data Science
  • Distribution Functions
  • Efficiency
  • Estimators
  • Information Science
  • Military Research
  • Normal Distribution
  • Normality
  • Order Statistics
  • Probability
  • Security
  • Sequences
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Statistical inference.